Files
pipeline/disk_postprocess.py
T
2020-12-14 16:22:42 +01:00

1029 lines
30 KiB
Python

# coding: utf-8
import sys
import numpy as np
import os
import pymses
import matplotlib as mpl
if os.environ.get("DISPLAY", "") == "":
print("No display found. Using non-interactive Agg backend")
mpl.use("Agg")
import pylab as P
import glob as glob
import pickle as pickle
from pymses.sources.ramses import output
from pymses.analysis import Camera, raytracing, slicing, splatting
from pymses.filters import CellsToPoints
from pymses.analysis import ScalarOperator, FractionOperator, MaxLevelOperator
# extension for out files
out_ext = ".jpeg"
P.rcParams["image.cmap"] = "plasma"
P.rcParams["savefig.dpi"] = 400
def make_image_disk(
path,
num,
path_out=None,
order="<",
force=False,
tag="",
vel_red=20,
map_size=512,
put_title=True,
cpuamr=False,
cpu=False,
level=False,
pos_star=np.array([1.0, 1.0, 1.0]),
interactive=False,
fft=False,
):
"""
Make several useful image of an output of a simulation
Parameters
----------
path path of the Ramses output
num Ramses output number
path_out path of the pipeline outputb
order '<' or '>' TODO
force if set, erase any existing pipeline output files
tag string to add to the output name
vel_red number of point where velocity should be plot in the slices
map_size size of the map
cpuamr plot also levels and cpus at each step
"""
ro = pymses.RamsesOutput(path, num, order=order)
amr = ro.amr_source(["rho", "vel", "P"])
rad = 0.5
center = [0.5, 0.5, 0.5]
make_image_aux(
amr,
ro,
center,
rad,
num,
path,
force=force,
path_out=path_out,
map_size=map_size,
vel_red=vel_red,
tag=tag,
cpuamr=cpuamr,
cpu=cpu,
level=level,
put_title=put_title,
pos_star=pos_star,
interactive=interactive,
fft=fft,
)
def make_image_aux(
amr,
ro,
center,
radius,
num,
path,
force=False,
path_out=None,
map_size=512,
vel_red=20,
tag="",
cpuamr=False,
cpu=False,
level=False,
pos_star=np.array([1.0, 1.0, 1.0]),
put_title=True,
interactive=False,
fft=False,
):
"""
Make several useful image of an output of a simulation, auxillary function
Parameters
----------
amr
ro pymses.RamsesOutput object
center 3D array for coordinates center
num output number
path_out path of the pipeline output
force if set, erase any existing pipeline output files
tag string to add to the output name
vel_red number of point where velocity should be plot in the slices
map_size size of the map
cpuamr plot also levels and cpus at each step
"""
cpu = cpu or cpuamr
level = level or cpuamr
lbox = ro.info["boxlen"] # boxlen in codeunits
lbox_units = lbox
G = 1.0 # Gravitational constant
# Plotting parameters
ntick = 6
title_ax = {"x": "x (code)", "y": "y (code)", "z": "z (code)"}
im_extent = [
(-radius + center[0]) * lbox_units,
(radius + center[0]) * lbox_units,
(-radius + center[1]) * lbox_units,
(radius + center[1]) * lbox_units,
]
time = ro.info["time"] # time in codeunits
title = "t=" + str(time)[0:5] + " (code)"
if path_out is not None:
directory = path_out
else:
directory = path
name = directory + "/coldens_z" + "_" + tag + "_" + format(num, "05") + out_ext
if len(glob.glob(name)) == 1 and not force:
return
rho_op = ScalarOperator(lambda dset: dset["rho"], ro.info["unit_density"])
rt = None
if fft:
rt = splatting.SplatterProcessor(amr, ro.info, rho_op)
else:
rt = raytracing.RayTracer(amr, ro.info, rho_op)
axes_los = ["x", "y", "z"] # Line of sight axes
axes_h = ["y", "x", "x"] # Horizontal axes
axes_v = ["z", "z", "y"] # Vertical axes
ax_nb = {"x": 0, "y": 1, "z": 2}
for i, ax_los in enumerate(axes_los):
ax_h = axes_h[i]
ax_v = axes_v[i]
cam = Camera(
center=center,
line_of_sight_axis=ax_los,
region_size=[2.0 * radius, 2.0 * radius],
distance=radius,
far_cut_depth=radius,
up_vector=ax_v,
map_max_size=map_size,
)
if interactive:
P.figure()
else:
P.close()
# Levels
if level:
level_op = MaxLevelOperator()
amr.set_read_levelmax(20)
rt_level = raytracing.RayTracer(amr, ro.info, level_op)
datamap = rt_level.process(cam, surf_qty=True)
map_level = datamap.map.T
levels_ar = np.arange(ro.info["levelmin"], ro.info["levelmax"] + 1)
# Computing linewidths
lw = np.ones(levels_ar.size) * 2
lvl_th = 8
lw[levels_ar >= lvl_th] = lw[levels_ar >= lvl_th] ** (
lvl_th - levels_ar[levels_ar >= lvl_th]
)
lw[levels_ar < lvl_th] = 1.0
cont = P.contour(
map_level,
extent=im_extent,
origin="lower",
colors="k",
linewidths=lw,
levels=levels_ar,
)
cont.levels = cont.levels + 1
P.clabel(
cont,
levels_ar[levels_ar < lvl_th + 2][1::2],
inline=1,
fontsize=8.0,
fmt="%1d",
)
# Column density
datamap = rt.process(cam, surf_qty=True)
dmap_col = datamap.map.T * lbox
map_col = np.log10(dmap_col)
im = P.imshow(map_col, extent=im_extent, origin="lower")
P.locator_params(axis=ax_h, nbins=ntick)
P.locator_params(axis=ax_v, nbins=ntick)
if put_title:
P.title(title)
P.xlabel(title_ax[ax_h])
P.ylabel(title_ax[ax_v])
cbar = P.colorbar(im)
cbar.set_label(r"$log(N)$ (code)")
name = directory + "/coldens_" + ax_los + "_" + tag + "_" + format(num, "05")
name_im = name + out_ext
if interactive:
P.figure()
else:
P.savefig(name_im)
P.close()
# Rho slice
dmap_rho = slicing.SliceMap(amr, cam, rho_op, z=0.0)
map_rho = np.log10(dmap_rho.map)
map_rho = map_rho.T
vh_op = ScalarOperator(
lambda dset: dset["vel"][:, ax_nb[ax_h]], ro.info["unit_velocity"]
)
dmap_vh = slicing.SliceMap(amr, cam, vh_op, z=0.0)
map_vh_red = dmap_vh.map[
::vel_red, ::vel_red
] # take only a subset of velocities
map_vh_red = map_vh_red.T
vv_op = ScalarOperator(
lambda dset: dset["vel"][:, ax_nb[ax_v]], ro.info["unit_velocity"]
)
dmap_vv = slicing.SliceMap(amr, cam, vv_op, z=0.0)
map_vv_red = dmap_vv.map[::vel_red, ::vel_red]
map_vv_red = map_vv_red.T
im = P.imshow(map_rho, extent=im_extent, origin="lower")
P.locator_params(axis=ax_h, nbins=ntick)
P.locator_params(axis=ax_v, nbins=ntick)
nh = map_vh_red.shape[0]
nv = map_vv_red.shape[1]
vec_h = (
np.arange(nh) * 2.0 / nh * radius - radius + center[0] + radius / nh
) * lbox_units
vec_v = (
np.arange(nv) * 2.0 / nv * radius - radius + center[1] + radius / nv
) * lbox_units
hh, vv = np.meshgrid(vec_h, vec_v)
max_v = np.max(np.sqrt(map_vh_red ** 2 + map_vv_red ** 2))
Q = P.quiver(hh, vv, map_vh_red, map_vv_red, units="width")
P.quiverkey(
Q,
0.7,
0.95,
max_v,
r"$" + str(max_v)[0:4] + "$ (code)",
labelpos="E",
coordinates="figure",
)
if put_title:
P.title(title)
P.xlabel(title_ax[ax_h])
P.ylabel(title_ax[ax_v])
cbar = P.colorbar(im)
cbar.set_label(r"$log(n)$ (code)")
name = directory + "/rho_" + ax_los + "_" + tag + "_" + format(num, "05")
name_im = name + out_ext
if interactive:
P.figure()
else:
P.savefig(name_im)
P.close()
P_op = ScalarOperator(lambda dset: dset["P"], ro.info["unit_pressure"])
dmap_P = slicing.SliceMap(amr, cam, P_op, z=0.0)
dmap_T = dmap_P.map.T / dmap_rho.map.T
map_T = np.log10(dmap_T)
im = P.imshow(map_T, extent=im_extent, origin="lower")
P.locator_params(axis="x", nbins=ntick)
P.locator_params(axis="y", nbins=ntick)
if put_title:
P.title(title)
P.xlabel(title_ax[ax_h])
P.ylabel(title_ax[ax_v])
cbar = P.colorbar(im)
cbar.set_label(r"$log(T) \, (K)$")
name = directory + "/T_" + ax_los + "_" + tag + "_" + format(num, "05")
name_im = name + out_ext
if interactive:
P.figure()
else:
P.savefig(name_im)
P.close()
# Toomre parameter
if ax_los == "z":
def omega_rho_func(dset):
pos = dset.get_cell_centers()
pos = pos - (pos_star / lbox)
xx = pos[:, :, 0]
yy = pos[:, :, 1]
rc = np.sqrt(xx ** 2 + yy ** 2) # cylindrical radius
vx = dset["vel"][:, :, 0]
vy = dset["vel"][:, :, 1]
omega_rho = 1.0 / rc ** 2
omega_rho = omega_rho * dset["rho"]
vyx = vy * xx
vxy = vx * yy
omega_rho = omega_rho * (vyx - vxy)
return omega_rho
omega_op = FractionOperator(
omega_rho_func, lambda dset: dset["rho"], 1.0 / ro.info["unit_time"]
)
cs_op = FractionOperator(
lambda dset: dset["P"],
lambda dset: dset["rho"],
ro.info["unit_velocity"],
)
rt_omega = raytracing.RayTracer(amr, ro.info, omega_op)
if fft:
rt_cs = splatting.SplatterProcessor(amr, ro.info, cs_op, surf_qty=False)
else:
rt_cs = raytracing.RayTracer(amr, ro.info, cs_op)
dmap_omega = rt_omega.process(cam)
dmap_cs = rt_cs.process(cam)
dmap_Q = (lbox * dmap_cs.map.T) * dmap_omega.map.T / (np.pi * G * dmap_col)
map_Q = dmap_Q
im = P.imshow(
map_Q, extent=im_extent, origin="lower", norm=mpl.colors.LogNorm()
)
P.locator_params(axis="x", nbins=ntick)
P.locator_params(axis="y", nbins=ntick)
if put_title:
P.title(title)
P.xlabel(title_ax[ax_h])
P.ylabel(title_ax[ax_v])
cbar = P.colorbar(im)
cbar.set_label(r"$Q$")
name = directory + "/Q_" + ax_los + "_" + tag + "_" + format(num, "05")
name_im = name + out_ext
if interactive:
P.figure()
else:
P.savefig(name_im)
P.close()
if cpu:
cpu_op = ScalarOperator(
lambda dset: dset.icpu * (np.ones(dset["P"].shape)),
ro.info["unit_pressure"],
)
rt_cpu = raytracing.RayTracer(amr, ro.info, cpu_op)
datamap = rt_cpu.process(cam, surf_qty=True)
map_cpu = datamap.map.T
im = P.imshow(map_cpu, extent=im_extent, origin="lower")
P.locator_params(axis="x", nbins=ntick)
P.locator_params(axis="y", nbins=ntick)
if put_title:
P.title(title)
P.xlabel(title_ax[ax_h])
P.ylabel(title_ax[ax_v])
cbar = P.colorbar(im)
cbar.set_label(r"cpu")
name = directory + "/cpu_" + ax_los + "_" + tag + "_" + format(num, "05")
name_im = name + out_ext
if interactive:
P.figure()
else:
P.savefig(name_im)
P.close()
def disk_prop(
path_in,
num,
path_out=None,
force=False,
nb_bin=20,
rad_ext=1.0,
mass_star=1.0,
pos_star=np.array([1.0, 1.0, 1.0]),
):
"""
Compute properties of a disk in the plane (0,x,y)
with a protostar at the center of the box
The region of the disk is defined by its scale height
Parameters
----------
path_in path of the input data files (output of ramses)
num id of the output
path_out optional path to the output files
force if set, redo ouptut even if already done
nb_bin Number of radial bins
rad_ext Outer radius of the disk
pos_star position of the central protostar
mass_star mass of the central protostar
"""
# Set th output directory
if path_out is not None:
directory_out = path_out
else:
directory_out = path_in
# Check if the output file exists, and exit if it is the case
name_save = directory_out + "/prop_disk_" + str(num).zfill(5) + ".save"
if not force and len(glob.glob(name_save)) != 0:
return
nb_bin_hist = nb_bin
# Compute the bins array
lrad = np.log10(rad_ext)
rad = np.logspace(lrad - 2.0, lrad, num=nb_bin)
# Get Ramses data
ro = pymses.RamsesOutput(path_in, num)
lbox = ro.info["boxlen"] # boxlen in codeunits (=>pc)
time = ro.info["time"] # time in codeunits
# Get array of cell positions
amr = ro.amr_source(["rho", "vel", "Br", "Bl", "P", "g", "phi"])
cell_source = CellsToPoints(amr)
cells = cell_source.flatten()
dx = cells.get_sizes() * lbox
pos = cells.points * lbox
# Get positions in the frame of the protostar
pos = pos - pos_star
# Get cylindrical radius
rc = np.sqrt(pos[:, 0] ** 2 + pos[:, 1] ** 2)
# Get velocities
vel = cells["vel"]
# Get radial component of velocity
norm_pos = rc
norm_pos[rc == 0] = 1.0e-10 # Avoid division per 0
v_rad = (pos[:, 0] * vel[:, 0] + pos[:, 1] * vel[:, 1]) / norm_pos
# Get azimuthal component of velocity
v_az = (pos[:, 0] * vel[:, 1] - pos[:, 1] * vel[:, 0]) / norm_pos
# Gravitational field
g = cells["g"]
g_rad = (pos[:, 0] * g[:, 0] + pos[:, 1] * g[:, 1]) / norm_pos
g_az = (pos[:, 0] * g[:, 1] - pos[:, 1] * g[:, 0]) / norm_pos
# Select cells that are actually in the disk, ie within the scale height
G = 1.0
cs = np.sqrt(cells["P"] / cells["rho"]) # sound velocity
height = cs * np.sqrt(rc ** 3 / (G * mass_star))
mask_pos = np.abs(pos[:, 2]) < height # condition on position
mask_dens = cells["rho"] > 1.0e6 # condition on density
mask = mask_pos # & mask_dens
print("Number of selected cells ", np.sum(mask))
pos_disk = pos[mask]
rc_disk = rc[mask]
vel_disk = vel[mask]
rho_disk = cells["rho"][mask] # density
press_disk = cells["P"][mask] # pressure
dx_disk = dx[mask]
dvol_disk = dx_disk ** 3
v_rad_disk = v_rad[mask]
v_az_disk = v_az[mask]
v_kepl = np.sqrt(mass_star * G / rc_disk)
height_disk = height[mask]
g_rad_disk = g_rad[mask]
g_az_disk = g_az[mask]
total_mass_disk = np.sum(rho_disk * dvol_disk)
total_mass = np.sum(cells["rho"] * dx ** 3)
print("Mass disk", total_mass_disk)
print("Mass box", total_mass)
# Initialize binned quantities
cs_rad = np.zeros(nb_bin - 1)
temp_rad = np.zeros(nb_bin - 1)
press_rad = np.zeros(nb_bin - 1)
rho_rad = np.zeros(nb_bin - 1)
coldens_rad = np.zeros(nb_bin - 1)
v_az_rad = np.zeros(nb_bin - 1)
v_kepl_rad = np.zeros(nb_bin - 1)
v_rad_rad = np.zeros(nb_bin - 1)
alpha_rey_rad = np.zeros(nb_bin - 1)
alpha_rey_rad_bis = np.zeros(nb_bin - 1)
alpha_grav_rad = np.zeros(nb_bin - 1)
Q_kepl_rad = np.zeros(nb_bin - 1)
height_rad = np.zeros(nb_bin - 1)
vol_rad = np.zeros(nb_bin - 1) # Volume of a bin
surf_rad = np.zeros(nb_bin - 1) # Surface of a bin
mass_rad = np.zeros(nb_bin - 1) # Mass of a bin
# Density fluctuations
hist_drho = np.zeros(nb_bin_hist)
hist_edges = np.zeros(nb_bin_hist + 1)
for i in range(nb_bin - 1):
mask_bin = (rc_disk > rad[i]) & (rc_disk < rad[i + 1])
# print("Bin #{} : {} cells between {} and {}".format(i, np.sum(mask_bin), rad[i], rad[i + 1]))
vol_rad[i] = np.sum(dvol_disk[mask_bin])
mass_rad[i] = np.sum(rho_disk[mask_bin] * dvol_disk[mask_bin])
press_rad[i] = np.sum(press_disk[mask_bin] * dvol_disk[mask_bin]) / vol_rad[i]
rho_rad[i] = np.sum(rho_disk[mask_bin] * dvol_disk[mask_bin]) / vol_rad[i]
temp_rad[i] = np.sum(press_disk[mask_bin] * dvol_disk[mask_bin]) / mass_rad[i]
# Surface of a bin : S = dr * 2 * pi * r with
# dr = rad[i + 1] - rad[i] and r = (rad[i + 1] + rad[i]) / 2.
surf_rad[i] = (rad[i + 1] - rad[i]) * (rad[i + 1] + rad[i]) * np.pi
coldens_rad[i] = mass_rad[i] / surf_rad[i]
v_az_rad[i] = (
np.sum(v_az_disk[mask_bin] * rho_disk[mask_bin] * dvol_disk[mask_bin])
/ mass_rad[i]
)
v_rad_rad[i] = (
np.sum(v_rad_disk[mask_bin] * rho_disk[mask_bin] * dvol_disk[mask_bin])
/ mass_rad[i]
)
height_rad[i] = (
np.sum(height_disk[mask_bin] * rho_disk[mask_bin] * dvol_disk[mask_bin])
/ mass_rad[i]
)
alpha_rey_rad[i] = (2.0 / 3) * (
(
np.sum(
v_az_disk[mask_bin]
* v_rad_disk[mask_bin]
* rho_disk[mask_bin]
* dvol_disk[mask_bin]
)
/ np.sum(dvol_disk[mask_bin] * press_disk[mask_bin])
- v_az_rad[i] * v_rad_rad[i] * rho_rad[i] / press_rad[i]
)
* v_az_rad[i]
/ abs(v_az_rad[i])
)
alpha_grav_rad[i] = (2.0 / 3) * (
np.sum(
g_az_disk[mask_bin]
* g_rad_disk[mask_bin]
* rho_disk[mask_bin]
* dvol_disk[mask_bin]
)
/ (4 * np.pi * G)
/ np.sum(dvol_disk[mask_bin] * press_disk[mask_bin])
* coldens_rad[i]
)
v_kepl_rad[i] = (
np.sum(v_kepl[mask_bin] * rho_disk[mask_bin] * dvol_disk[mask_bin])
/ mass_rad[i]
)
# Histogramm : density fluctuaction distribution function
drho = np.log(rho_disk[mask_bin] / rho_rad[i])
hist, hist_edges = P.histogram(
drho, bins=nb_bin_hist, weights=dvol_disk[mask_bin]
)
hist_drho = hist_drho + hist
# Derived quantities
cs_rad = np.sqrt(temp_rad)
Q_kepl_rad = cs_rad * v_az_rad / (np.pi * G * coldens_rad * rad[0 : nb_bin - 1])
# Means
mask_mean = (0.1 < rad[0 : nb_bin - 1]) & (rad[0 : nb_bin - 1] < 0.2)
print(rad[0 : nb_bin - 1][mask_mean])
mass_mean = np.sum(mass_rad[mask_mean])
alpha_rey_mean = np.sum(alpha_rey_rad[mask_mean] * mass_rad[mask_mean]) / mass_mean
alpha_grav_mean = (
np.sum(alpha_grav_rad[mask_mean] * mass_rad[mask_mean]) / mass_mean
)
Q_mean = np.sum(Q_kepl_rad[mask_mean] * mass_rad[mask_mean]) / mass_mean
Q_min = np.nanmin(Q_kepl_rad)
print("alphas, Q ", alpha_rey_mean, alpha_grav_mean, Q_mean)
# store the results
prop_disk = {
"time": time,
"mass_disk": total_mass_disk,
"mass_box": total_mass,
"rad": rad[0 : nb_bin - 1],
"center": pos_star,
"alpha_rey": alpha_rey_rad,
"alpha_rey_mean": alpha_rey_mean,
"alpha_grav": alpha_grav_rad,
"alpha_grav_mean": alpha_grav_mean,
"v_rad": v_rad_rad,
"v_az": v_az_rad,
"v_kepl": v_kepl_rad,
"coldens": coldens_rad,
"rho": rho_rad,
"press": press_rad,
"hist_drho": hist_drho,
"hist_edges": hist_edges,
"temp": temp_rad,
"cs": cs_rad,
"Q_kepl": Q_kepl_rad,
"Q_mean": Q_mean,
"Q_min": Q_min,
"height": height_rad,
}
f = open(name_save, "w")
pickle.dump(prop_disk, f)
f.close()
def plot_disk_prop(path, num, force=False, tag="", interactive=False):
"""
Plot properties of a disk
num id of the ramses output
path path to the properties file
force if set, redo plots even if already done
"""
# Load property file
name_save = path + "/prop_disk_" + str(num).zfill(5) + ".save"
# Check if the properties file exists
if len(glob.glob(name_save)) == 0:
raise ("no pickle file for disk properties. Run disk_prop() first")
f = open(name_save, "r")
prop_disk = pickle.load(f)
f.close()
# Check if the output file exists, and exit if it is the case
name_save = path + "/rho_disk_r_" + str(num).zfill(5) + out_ext
if not force and len(glob.glob(name_save)) != 0:
return
time = prop_disk["time"]
mass = prop_disk["mass_disk"]
title = "t=" + str(time)[0:5] + " (code)"
rad = prop_disk["rad"]
if interactive:
P.figure()
else:
P.close()
P.xscale("log")
P.yscale("log")
P.grid()
P.plot(rad, prop_disk["rho"], color="k", linewidth=2)
P.ylabel(r"$n \, (code)$")
P.xlabel("disk radius")
P.title(title)
if interactive:
P.figure()
else:
P.savefig(path + "/rho_disk_r_" + str(num).zfill(5) + out_ext)
P.close()
P.xscale("log")
P.yscale("log")
P.grid()
P.plot(rad, prop_disk["temp"], color="k", linewidth=2)
P.ylabel(r"$T \, (K)$")
P.xlabel("disk radius")
P.title(title)
if interactive:
P.figure()
else:
P.savefig(path + "/T_disk_r_" + str(num).zfill(5) + out_ext)
P.close()
P.xscale("log")
P.yscale("symlog", linthreshy=0.01)
P.plot(rad, prop_disk["v_rad"], color="k", linewidth=2)
P.plot(rad, prop_disk["v_kepl"], color="b", linewidth=2)
P.plot(rad, abs(prop_disk["v_az"]), color="r", linewidth=2)
P.plot(rad, prop_disk["cs"], color="c", linewidth=2)
P.grid()
P.legend((r"$v_r$", r"$v_{kepl}$", r"$v_\phi$", r"$c_s$"), loc="upper right")
P.ylabel(r"$V \, (km s^{-1})$")
P.xlabel("disk radius")
if interactive:
P.figure()
else:
P.savefig(path + "/V_disk_r_" + str(num).zfill(5) + out_ext)
P.close()
P.xscale("log")
P.yscale("log")
P.grid()
P.plot(rad, prop_disk["coldens"], color="k", linewidth=2)
P.ylabel(r"$N\, (cm^{-2})$")
P.xlabel("disk radius ")
P.title(title)
if interactive:
P.figure()
else:
P.savefig(path + "/coldens_disk_r_" + str(num).zfill(5) + out_ext)
P.close()
# Alpha
alpha_rey_mean, alpha_grav_mean = (
prop_disk["alpha_rey_mean"],
prop_disk["alpha_grav_mean"],
)
# P.xscale('log')
P.xlim([1e-2, 0.25])
P.yscale("log")
P.ylim([1e-7, 1.0])
P.grid()
P.plot(
rad, abs(prop_disk["alpha_rey"]), "b", linewidth=2, label=r"$\alpha_{Reynolds}$"
)
P.plot(rad, abs(alpha_rey_mean * np.ones(len(rad))), "b:", linewidth=1)
P.plot(
rad, abs(prop_disk["alpha_grav"]), "r", linewidth=2, label=r"$\alpha_{grav}$"
)
P.plot(rad, abs(alpha_grav_mean * np.ones(len(rad))), "r:", linewidth=1)
P.plot(
rad,
abs(prop_disk["alpha_rey"]) + abs(prop_disk["alpha_grav"]),
"g--",
linewidth=2,
label=r"$\alpha_{tot}$",
)
P.title(
title
+ r", $\bar{\alpha}_{Reynolds} = %.1e, \bar{\alpha}_{grav} = %.1e$"
% (alpha_rey_mean, alpha_grav_mean)
)
P.legend()
P.ylabel(r"$\alpha$")
P.xlabel("disk radius ")
if interactive:
P.figure()
else:
P.savefig(path + "/alpha_disk_r_" + str(num).zfill(5) + out_ext)
P.close()
# Q
P.ylim([0, 10.0])
P.xlim([0, 0.5])
P.yticks(np.arange(0.0, 11, 1.0))
P.grid()
P.plot(rad, abs(prop_disk["Q_kepl"]), color="b", linewidth=2)
P.plot(rad, abs(prop_disk["Q_mean"]) * np.ones(len(rad)), "b:", linewidth=1)
P.ylabel(r"$Q$")
P.xlabel("disk radius ")
P.title(title + ", mass of disk = {} (code)".format(mass))
if interactive:
pass
else:
P.savefig(path + "/Q_r_" + str(num).zfill(5) + out_ext)
P.close()
# height ratio
P.grid()
P.plot(rad, abs(prop_disk["height"] / rad), color="b", linewidth=2)
P.ylabel(r"H ratio")
P.xlabel("disk radius ")
P.title(title + ", mass of box = {} (code)".format(prop_disk["mass_box"]))
if interactive:
pass
else:
P.savefig(path + "/H_r_" + str(num).zfill(5) + out_ext)
P.close()
# Density fluctuation histogram
P.grid()
P.xlabel(r"$\log(\frac{\rho}{\bar{\rho}})$")
P.ylabel(r"fraction of total volume")
P.title(title)
hist = prop_disk["hist_drho"]
egdes = prop_disk["hist_edges"]
widths = egdes[1:] - egdes[:-1]
centers = egdes[:-1] + widths / 2.0
P.bar(centers, hist, width=widths)
if interactive:
pass
else:
P.savefig(path + "/drho_hist_" + str(num).zfill(5) + out_ext)
P.close()
def compare(path, runs, num, force=False, interactive=False):
"""
Compare properties of a disk in several simulations
num id of the ramses output
runs list of runs to consider
path path to the properties file
force if set, redo plots even if already done
interactive interactive mode, to use in a %pylab ipython shell
"""
# Initialize arrays
time = np.zeros(len(runs))
alpha_rey = np.zeros(len(runs))
alpha_grav = np.zeros(len(runs))
Q = np.zeros(len(runs))
Q0 = np.zeros(len(runs))
for i, run in enumerate(runs):
path_run = path + "/" + run
# Load property file
name_save = path_run + "/prop_disk_" + str(num).zfill(5) + ".save"
# Check if the properties file exists
if len(glob.glob(name_save)) == 0:
raise ("no pickle file for disk properties. Run disk_prop() first")
f = open(name_save, "r")
prop_disk = pickle.load(f)
f.close()
time[i] = prop_disk["time"]
alpha_rey[i] = prop_disk["alpha_rey_mean"]
alpha_grav[i] = prop_disk["alpha_grav_mean"]
Q[i] = prop_disk["Q_min"]
Q0[i] = float(run.split("_")[2][1:])
# Check if the output file exists, and exit if it is the case
name_save = path + "/alphaQ_" + str(num).zfill(5) + out_ext
if not force and len(glob.glob(name_save)) != 0:
return
title = "t=" + str(time[0]) + " (code)"
# alpha = f(Qmin)
P.yscale("log")
P.ylim([1e-7, 1.0])
P.grid()
P.plot(Q, abs(alpha_rey), "o--", label=r"$\bar{\alpha}_{Reynolds}$")
P.plot(Q, abs(alpha_grav), "*--", label=r"$\bar{\alpha}_{grav}$")
P.legend()
P.ylabel(r"$\bar{\alpha}$")
P.xlabel(r"$Q_{min}$")
if interactive:
P.figure()
else:
P.savefig(path + "/alphaQ_" + str(num).zfill(5) + out_ext)
P.close()
# alpha = f(Q0)
P.yscale("log")
P.ylim([1e-7, 1.0])
P.grid()
P.plot(Q0, abs(alpha_rey), "o-.", label=r"$\bar{\alpha}_{Reynolds}$")
P.plot(Q0, abs(alpha_grav), "*--", label=r"$\bar{\alpha}_{grav}$")
P.legend()
P.ylabel(r"$\bar{\alpha}$")
P.xlabel(r"$Q_{0}$")
if interactive:
P.figure()
else:
P.savefig(path + "/alphaQ0_" + str(num).zfill(5) + out_ext)
P.close()
def evolution(path, nums, force=False, interactive=False):
"""
Plot properties over time
path path to the properties file
nums list of id of the ramses output
force if set, redo plots even if already done
interactive interactive mode, to use in a %pylab ipython shell
"""
# Initialize arrays
time = np.zeros(len(nums))
alpha_rey = np.zeros(len(nums))
alpha_grav = np.zeros(len(nums))
Qmin = np.zeros(len(nums))
Qmean = np.zeros(len(nums))
mass_disk = np.zeros(len(nums))
mass_box = np.zeros(len(nums))
for i, num in enumerate(nums):
# Load property file
name_prop = path + "/prop_disk_" + str(num).zfill(5) + ".save"
# Check if the properties file exists
if len(glob.glob(name_prop)) == 0:
raise ("no pickle file for disk properties. Run disk_prop() first")
f = open(name_prop, "r")
prop_disk = pickle.load(f)
f.close()
time[i] = prop_disk["time"]
alpha_rey[i] = prop_disk["alpha_rey_mean"]
alpha_grav[i] = prop_disk["alpha_grav_mean"]
Qmin[i] = prop_disk["Q_min"]
Qmean[i] = prop_disk["Q_mean"]
mass_disk[i] = prop_disk["mass_disk"]
mass_box[i] = prop_disk["mass_box"]
# Check if the output file exists, and exit if it is the case
name_save = path + "/alpha_time" + out_ext
if not force and len(glob.glob(name_save)) != 0:
return
# Alpha
P.yscale("log")
P.ylim([1e-7, 1.0])
P.grid()
P.plot(time, abs(alpha_rey), "o-.", label=r"$\bar{\alpha}_{Reynolds}$")
P.plot(time, abs(alpha_grav), "*--", label=r"$\bar{\alpha}_{grav}$")
P.legend()
P.ylabel(r"$\bar{\alpha}$")
P.xlabel(r"time (code)")
if interactive:
P.figure()
else:
P.savefig(path + "/alpha_time" + out_ext)
P.close()
# Q
P.grid()
P.plot(time, Qmin, "o-.", label=r"$Q_{min}$")
P.plot(time, Qmean, "*--", label=r"$\bar{Q}$")
P.legend()
P.ylabel(r"$Q$")
P.xlabel(r"time (code)")
if interactive:
P.figure()
else:
P.savefig(path + "/Q_time" + out_ext)
P.close()
# M
P.grid()
P.plot(time, mass_disk, "o-.", label=r"$M_{disk}$")
P.plot(time, mass_box, "*--", label=r"$M_{box}$")
P.legend()
P.ylabel(r"$M / M_{*}$")
P.xlabel(r"time (code)")
if interactive:
P.figure()
else:
P.savefig(path + "/mass_time" + out_ext)
P.close()